load libraries
library("tidyverse")
library("plyr")
library("dplyr")
library("ggplot2")
library("RColorBrewer")
#library("scales")
#library("ggpubr")
#library("gridExtra")
#library("grid")
#library("GGally")
library("data.table")
library("stringr")
library("janitor")
library("knitr")
library("kableExtra")
library("plotly") # for the 3d plots
knitr::opts_chunk$set(echo = TRUE, warning = FALSE, message = FALSE)
# fig.width = 20,
# fig.asp = 0.6,
# out.width = "100%")
data <- read.csv("/Users/nuriteliash/Documents/GitHub/varroa_ploidy/data/ploidy.csv") %>%
dplyr::mutate(Family = as.character(Family))
# order the levels
data$body.part <- factor(data$body.part, level=c("Body", "Anterior", "Posterior", "Legs","Hemolymph","Ovary","Testes"))
data$Stage <- factor(data$Stage, level=c("Larvae", "Protonymph", "Deuteronymph", "adult"))
p_fem = data %>% dplyr::filter(Sex == "fem") %>%
dplyr::filter(body.part == c("Body", "Legs","Ovary","Testes")) %>%
ggplot(aes(y=ploidy, x=body.part, fill = Sex)) +
geom_boxplot() + theme_classic() + geom_jitter(width=0.1, size=2) +
facet_wrap(~Stage, nrow = 1) + ggtitle('Female mite ploidy') +
ylim(0, 3)
p_male = data %>% dplyr::filter(Sex == "male") %>%
dplyr::filter(body.part == c("Body", "Legs","Ovary","Testes")) %>%
ggplot(aes(y=ploidy, x=body.part, fill = Sex)) +
geom_boxplot(fill = "#00AFBB") + theme_classic() + geom_jitter(width=0.1, size=2,color = "#00AFBB",fill = "#00AFBB") +
facet_wrap(~Stage, nrow = 1) + ggtitle('Male mite ploidy') +
ylim(0, 3)
p_adult = data %>% dplyr::filter(Stage == "adult") %>%
ggplot(aes(y=ploidy, x=body.part, fill = Sex, lable = Stage)) +
geom_boxplot(outlier.shape = NA, coef=0 ) + theme_classic() + geom_jitter(width=0.1, size=2) +
facet_wrap(~Sex) + ggtitle('Adult mite ploidy')
p_family = data %>% dplyr::filter(body.part == c("Body", "Ovary","Testes")) %>%
mutate_at("Family", ~replace_na(.,"0")) %>%
ggplot(aes(y=ploidy, x=Family, fill = Sex, lable = Stage)) +
geom_boxplot(outlier.shape = NA, coef=0 ) + theme_classic() + geom_jitter(width=0.1, size=2) +
facet_wrap(~body.part, ncol = 1 ) + ggtitle('Adult mite ploidy per family')
ggplotly(p_fem)
ggplotly(p_male)
ggplotly(p_adult)
ggplotly(p_family)